## An Extension of the ICP Algorithm for Modeling Nonrigid Objects with Mobile Robots

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@MISC{Hähnel_anextension,

author = {Dirk Hähnel and Sebastian Thrun and Wolfram Burgard},

title = {An Extension of the ICP Algorithm for Modeling Nonrigid Objects with Mobile Robots},

year = {}

}

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### Abstract

The iterative closest point (ICP) algorithm [2] is a popular method for modeling 3D objects from range data. The classical ICP algorithm rests on a rigid surface assumption. Building on recent work on nonrigid object models [5, 16, 9] , this paper presents an ICP algorithm capable of modeling nonrigid objects, where individual scans may be subject to local deformations. We describe an integrated mathematical framework for simultaneously registering scans and recovering the surface configuration. To tackle the resulting...

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Citation Context ...(e.g., less than 10), the computationally most expensivesstep is the determination of the closest points in Step 2. This step is usually implemented efficiently by representing scans through kd-trees =-=[4]-=-. Figure 3a-b illustrate the result of scan registration in 2D. The initial configuration in Figure 3a is transformed into the one shown in Figure 3b, which is the one that minimizes the squared dista... |

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Citation Context ...am Burgard ‡† † Carnegie Mellon University, School of Computer Science, PA, USA, ‡ University of Freiburg, Department of Computer Science, Germany Abstract The iterative closest point (ICP) al=-=gorithm [2]-=- is a popular method for modeling 3D objects from range data. The classical ICP algorithm rests on a rigid surface assumption. Building on recent work on nonrigid object models [5; 16; 9], this paper ... |

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Citation Context ...egistration. Most state-of-the-art implementations are based on the popular iterative closest point algorithm [2]. The topic has received significant attention in fields as diverse as computer vision =-=[12; 9]-=- and medical imaging [7], large-scale urban modeling [14], and mobile robotics [10; 8; 15]. ICP aligns range scans by alternating a step in which closest points are identified, and a step by which the... |

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Citation Context ...closest point algorithm [2]. The topic has received significant attention in fields as diverse as computer vision [12; 9] and medical imaging [7], large-scale urban modeling [14], and mobile robotics =-=[10; 8; 15]-=-. ICP aligns range scans by alternating a step in which closest points are identified, and a step by which the optimal translation and rotation of scans relative to each other is computed. In doing so... |

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Citation Context ...closest point algorithm [2]. The topic has received significant attention in fields as diverse as computer vision [12; 9] and medical imaging [7], large-scale urban modeling [14], and mobile robotics =-=[10; 8; 15]-=-. ICP aligns range scans by alternating a step in which closest points are identified, and a step by which the optimal translation and rotation of scans relative to each other is computed. In doing so... |

237 | A new point matching algorithm for non-rigid registration
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Citation Context ...int (ICP) algorithm [2] is a popular method for modeling 3D objects from range data. The classical ICP algorithm rests on a rigid surface assumption. Building on recent work on nonrigid object models =-=[5; 16; 9]-=-, this paper presents an ICP algorithm capable of modeling nonrigid objects, where individual scans may be subject to local deformations. We describe an integrated mathematical framework for simultane... |

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Citation Context ...ink 1 − hi→j,k =; |2πΘ| 2 � exp − 1 2 � πjk − ˆπi→j,k rjk − ˆri→j,k �T Θ −1 � πjk − ˆπi→j,k rjk − ˆri→j,k � � Here Θ defines the strength of the link (t=-=he resulting structure is a Markov random field [17]). 3.2 Target Function -=-The negative logarithm of these potentials, summed over all links, is given by the following function H (constant omitted): H = 1 2 � i→j,k � πjk − ˆπi→j,k rjk − ˆri→j,k �T Θ −1... |

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Citation Context ...nts x [n+1] are now obtained through a closed-form solution of minimizing G [n] . This solution is obtained by setting the first derivative of G [n] with respect to x to zero (derivation omitted, see =-=[13]): x [n+1] = (Ψ ��-=-�1 + A [n]T Σ −1 A [n] ) −1 (Ψ −1 ¯x + A [n]T Σ −1 c [n] ) (16) In the original ICP algorithm [2], this step is implemented by calculating the the “center of mass” of each scan and shi... |

190 | An probabilistic online mapping algorithm for teams of mobile robots,” Int
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Citation Context ...closest point algorithm [2]. The topic has received significant attention in fields as diverse as computer vision [12; 9] and medical imaging [7], large-scale urban modeling [14], and mobile robotics =-=[10; 8; 15]-=-. ICP aligns range scans by alternating a step in which closest points are identified, and a step by which the optimal translation and rotation of scans relative to each other is computed. In doing so... |

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Citation Context ...s do trees, pillows, and so on. A natural research goal is therefore to extend ICP to accommodate local object transformations. Following recent work primarily found in the medical imaging literature =-=[5; 16; 6; 3]-=-, we proposes an approach suited for scan registration and 3D modeling of nonrigid objects that can efficiently deal with hundreds of thouFigure 1: The essential idea: Rather assuming that the relatio... |

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Citation Context ...int (ICP) algorithm [2] is a popular method for modeling 3D objects from range data. The classical ICP algorithm rests on a rigid surface assumption. Building on recent work on nonrigid object models =-=[5; 16; 9]-=-, this paper presents an ICP algorithm capable of modeling nonrigid objects, where individual scans may be subject to local deformations. We describe an integrated mathematical framework for simultane... |

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Citation Context ... on the popular iterative closest point algorithm [2]. The topic has received significant attention in fields as diverse as computer vision [12; 9] and medical imaging [7], large-scale urban modeling =-=[14]-=-, and mobile robotics [10; 8; 15]. ICP aligns range scans by alternating a step in which closest points are identified, and a step by which the optimal translation and rotation of scans relative to ea... |

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Citation Context ...o the problem of learning 3D models of non-stationary objects with a mobile robot. We describe an implemented robot system that utilizes a model differencing technique similar to the one described in =-=[1]-=- to segment scans. By acquiring views of the target objects from multiple sides, our approach enables a robot to acquire a 3D model of a non-stationary object. 2 Scan Registration This section describ... |

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Citation Context ...he-art implementations are based on the popular iterative closest point algorithm [2]. The topic has received significant attention in fields as diverse as computer vision [12; 9] and medical imaging =-=[7]-=-, large-scale urban modeling [14], and mobile robotics [10; 8; 15]. ICP aligns range scans by alternating a step in which closest points are identified, and a step by which the optimal translation and... |

18 |
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Citation Context ...s do trees, pillows, and so on. A natural research goal is therefore to extend ICP to accommodate local object transformations. Following recent work primarily found in the medical imaging literature =-=[5; 16; 6; 3]-=-, we proposes an approach suited for scan registration and 3D modeling of nonrigid objects that can efficiently deal with hundreds of thouFigure 1: The essential idea: Rather assuming that the relatio... |

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Citation Context ...= k � k l�=k 1 − |2πΨ| 2 exp � − 1 2 (xk − ¯xk) T Ψ −1 (xk − ¯xk) � In our robot system, this prior is obtained from the robot’s 2D localization routines, supplied by a public=-= domain software package [11].s(a) -=-initial registration (b) rigid object ICP (c) Θ = 10 I (d) Θ = 2 I (e) Θ = I (f) Θ = 10 −3 I Figure 3: Illustration in 2D: (a) initial configurations of two scans in red and blue, (b) result of ... |

3 | Surface Matching with Large Deformations and Arbitrary Topology: A Geodesic Distance Evolution Scheme on a 3-Manifold. ECCV
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Citation Context ...int (ICP) algorithm [2] is a popular method for modeling 3D objects from range data. The classical ICP algorithm rests on a rigid surface assumption. Building on recent work on nonrigid object models =-=[5; 16; 9]-=-, this paper presents an ICP algorithm capable of modeling nonrigid objects, where individual scans may be subject to local deformations. We describe an integrated mathematical framework for simultane... |